Transformer Health Condition Assessment Method Based on Full Life Cycle Data

Existing transformer condition assessment methods cover too few condition indicators and the assessment process relies on expert experience, making it difficult to guide field maintenance work. To address these problems, this paper proposes a transformer health condition assessment method based on full life cycle data. The method uses multi-dimensional, multi-structured, full life cycle data such as transformer operation information, online monitoring data, offline test data and operations and maintenance records as feature quantities, analyses the correlation between different condition indicators and transformer health status, constructs a fuzzy inference-based transformer health index calculation method, realises the quantitative rating of transformer health status, and verifies the method with field example analysis The feasibility and validity of the method were verified by combining with field cases. The results of the field application show that the method can effectively reflect the transformer operation status and has certain guiding significance for the field operation and maintenance decision.